Bioterrorism

Proteomics landscape and machine learning prediction of long-term response to splenectomy in primary immune thrombocytopenia.

This study aimed to identify key proteomic analytes correlated with response to splenectomy in prima...

Image-based artificial intelligence for the prediction of pathological complete response to neoadjuvant chemoradiotherapy in patients with rectal cancer: a systematic review and meta-analysis.

OBJECTIVE: Artificial intelligence (AI) holds enormous potential for noninvasively identifying patie...

Response to Letter to the Editor re: "Artificial Intelligence Versus Expert Plastic Surgeon: Comparative Study Shows ChatGPT 'Wins' Rhinoplasty Consultations: Should We Be Worried? [1]" by Durairaj et al.

Non-invasive assessment of response to transcatheter arterial chemoembolization for hepatocellular carcinoma with the deep neural networks-based radiomics nomogram.

BACKGROUND: Transcatheter arterial chemoembolization (TACE) is a mainstay treatment for intermediate...

Prediction of immunotherapy response in idiopathic membranous nephropathy using deep learning-pathological and clinical factors.

BACKGROUND: Owing to individual heterogeneity, patients with idiopathic membranous nephropathy (IMN)...

Artificial intelligence measured 3D body composition to predict pathological response in rectal cancer patients.

BACKGROUND: The treatment of locally advanced rectal cancer (LARC) is moving towards total neoadjuva...

A Baby Step or a Real Giant Stride: Histomic Enabled by Artificial Intelligence to Predict Treatment Response in Pediatric Patients With Ulcerative Colitis.

[Analysis of the challenges and dilemmas that bioethics of the 21st century will face in the digital health era].

The medical history underscores the significance of ethics in each advancement, with bioethics playi...

Building trust in deep learning-based immune response predictors with interpretable explanations.

The ability to predict whether a peptide will get presented on Major Histocompatibility Complex (MHC...

A deep learning model of tumor cell architecture elucidates response and resistance to CDK4/6 inhibitors.

Cyclin-dependent kinase 4 and 6 inhibitors (CDK4/6is) have revolutionized breast cancer therapy. How...

A machine learning approach for predicting treatment response of hyponatremia.

Hyponatremia leads to severe central nervous system disorders and requires immediate treatment in so...

Prediction of cognitive impairment using higher order item response theory and machine learning models.

Timely detection of cognitive impairment (CI) is critical for the wellbeing of elderly individuals. ...

Multimodal characterization of the collagen hydrogel structure and properties in response to physiologically relevant pH fluctuations.

pH fluctuations within the extracellular matrix (ECM) and its principal constituent collagen, partic...

Stratification of tumour cell radiation response and metabolic signatures visualization with Raman spectroscopy and explainable convolutional neural network.

Reprogramming of cellular metabolism is a driving factor of tumour progression and radiation therapy...

Response to Generative AI in Dental Licensing Examinations: Comment.

dbCRAF: a curated knowledgebase for regulation of radiation response in human cancer.

Radiation therapy (RT) is one of the primary treatment modalities of cancer, with 40-60% of cancer p...

Development and Preliminary Validation of a Novel Convolutional Neural Network Model for Predicting Treatment Response in Patients with Unresectable Hepatocellular Carcinoma Receiving Hepatic Arterial Infusion Chemotherapy.

The goal of this study was to evaluate the performance of a convolutional neural network (CNN) with ...

Optimal Enzyme-Assisted Extraction of Phenolics from Leaves of Pongamia pinnata via Response Surface Methodology and Artificial Neural Networking.

This research work seeks to evaluate the impact of selected enzyme complexes on the optimised releas...

Prediction of treatment response in major depressive disorder using a hybrid of convolutional recurrent deep neural networks and effective connectivity based on EEG signal.

In this study, we have developed a novel method based on deep learning and brain effective connectiv...

CuO/TiO/MXene-Based Sensor and SMS-TENG Array Integrated Inspection Robots for Self-Powered Ethanol Detection and Alarm at Room Temperature.

In this study, a high-precision CuO/TiO/MXene ethanol sensor operating at room temperature was prepa...

Exploring the role of large language models in radiation emergency response.

In recent times, the field of artificial intelligence (AI) has been transformed by the introduction ...